Software-defined infrastructure for identifying and remediating an airflow deficiency scenario on a rack device

ABSTRACT

A software-defined infrastructure can identify and remediate an airflow deficiency scenario on a rack device. A rack device manager can be configured to discover rack devices and create a representation of their physical locations. The rack device manager can also be configured to periodically retrieve airflow metrics of the rack devices to calculate an estimated airflow for each rack device. The rack device manager can use the estimated airflows and the airflow metrics to generate a rack device classifier for each rack device. Using these rack device classifiers, the rack device manager can detect when rack devices are experiencing airflow deficiencies and attempt to automatically remediate such deficiencies.

CROSS-REFERENCE TO RELATED APPLICATIONS

N/A

BACKGROUND

A server rack, or simply “rack,” is a structure for housing servers andother electronic equipment such as networking devices. A “rack device”is any electronic device, such as a server, that may be housed in arack. Racks are oftentimes located in data centers or other dedicatedrooms where the environment can be controlled to prevent overheating ofthe rack devices. For example, a data center may have a dedicatedcooling system to ensure that the ambient air temperature remainssufficiently cool to minimize the risk of overheating.

Even when the environment in which a rack is located may be adequatelycontrolled, it is still important to provide airflow to each rackdevice. For this reason, most rack devices include fans or othermechanisms for inducing airflow through or along the rack devices.However, airflow can still be inhibited for various reasons. Forexample, if a physical obstruction, such as a sticky note, is placed onthe front bezel of a rack device, which is where the air intake ventsare typically located, the airflow pattern can be altered thus causinghot air to recirculate in the rack device. A similar result may occur ifa physical obstruction is placed on the rack's door in front of a rackdevice.

As another example, one rack device's airflow can be reduced due to aneighboring rack device's airflow. For example, when a neighboring rackdevice is inducing excessive air intake, it can create an air void infront of the rack device. In such a case, even when the rack device'sfan is running, it may not be able to induce sufficient airflow to coolthe rack device due to the air void.

As a further example, even when there may be sufficient airflow for eachrack device, if the ambient air temperature is inadequately controlled,the rack devices may still overheat. For example, if the intake air isalready hot, it will provide minimal cooling to the rack device.

Various solutions exist for monitoring a rack device's temperature,airflow and other metrics. For example, some rack devices are configuredto control the fan speed based on air temperature, power consumption orother metrics. However, with such solutions, if increases in fan speeddo not adequately cool the rack device, it will be necessary to manuallyinspect the rack device to determine why inadequate cooling isoccurring. During such manual inspections, it is relatively easy toidentify a physical obstruction but rather difficult to identify an airvoid. Accordingly, even with existing solutions and manual inspections,it can be difficult to manage the cooling of rack devices.

BRIEF SUMMARY

The present invention extends to systems, methods and computer programproducts for providing a software-defined infrastructure for identifyingand remediating an airflow deficiency scenario on a rack device. A rackdevice manager can be configured to discover rack devices and create arepresentation of their physical locations. The rack device manager canalso be configured to periodically retrieve airflow metrics of the rackdevices to calculate an estimated airflow for each rack device. The rackdevice manager can use the estimated airflows and the airflow metrics togenerate a rack device classifier for each rack device. Using these rackdevice classifiers, the rack device manager can detect when rack devicesare experiencing airflow deficiencies and attempt to automaticallyremediate such deficiencies.

In some embodiments, the present invention may be implemented as amethod for identifying and remediating an airflow deficiency scenario ona rack device. It can be detected that a first rack device isexperiencing an airflow deficiency scenario. It can then be determinedthat a second rack device is a neighbor to the first rack device and hasexcess airflow. One or more actions can then be automatically performedto remediate the airflow deficiency scenario.

In some embodiments, the present invention may be implemented ascomputer storage media storing computer executable instructions whichwhen executed implement a method for identifying and remediating anairflow deficiency scenario on a rack device. Airflow metrics can beobtained from a plurality of rack devices. A rack device classifier canbe generated for each of the plurality of rack devices based on therespective airflow metrics. An airflow deficiency scenario can beidentified on at least one of the plurality of rack devices based on therespective rack device classifier. One or more actions can be performedto automatically remediate the airflow deficiency scenario.

In some embodiments, the present invention may be implemented as asystem for identifying and remediating an airflow deficiency scenario ona rack device. The system may include one or more processors and one ormore computer storage media storing computer executable instructionswhich when executed by the one or more processors implement a method foridentifying and remediating an airflow deficiency scenario on a rackdevice. A rack device classifier can be generated for each of theplurality of rack devices in a rack. It can be determined that the rackdevice classifier generated for a first rack device of the plurality ofrack devices is indicative of an airflow deficiency scenario. It canalso be determined that a second rack device of the plurality of rackdevices is a neighbor of the first rack device. One or more actions canthen be performed on the second rack device to automatically remediatethe airflow deficiency scenario.

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

Understanding that these drawings depict only typical embodiments of theinvention and are not therefore to be considered limiting of its scope,the invention will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 illustrates an example computing environment in which embodimentsof the present invention could be implemented;

FIGS. 2A-2C provide an example of how a rack device manager may identifyrack devices for which the rack device manager will provide airflowmanagement;

FIGS. 3A-3C provide an example of how a rack device manager can generatea rack device classifier for each rack device that it manages;

FIG. 4 provides an example of classifications that a rack deviceclassifier may have; and

FIGS. 5A-5E provide an example of how a rack device manager may use therack device classifiers to identify and remediate an airflow deficiencyscenario.

DETAILED DESCRIPTION

FIG. 1 illustrates an example computing environment 10 in whichembodiments of the present invention could be implemented. Computingenvironment 10 includes a rack device manager 100 and some number ofracks 110-1 through 110-n (individually or collectively rack(s) 110).

Each rack 110 can include a number of rack devices 111-1 through 111-n(individually and collectively rack device(s) 111). Rack devices 111could represent any type of device that may be housed in rack 110. Forexample, in some embodiments, devices 111 could all be servers. Asanother example, in some embodiments, devices 111 could include one ormore network devices such as switches, hubs, routers, modems, etc. Rackdevice manager 100 may be in the form of a service or other type ofsoftware component that runs on a computing device that has access todevices 111 in each rack 110. Rack device manager 100 can be configuredto identify and remediate an airflow deficiency scenario on any of rackdevices 111.

FIGS. 2A-2C provide an example of functionality that rack device manager100 may perform to identify rack devices for which it will provideairflow management. In some embodiments, an administrator may use aninterface provided by rack device manager 100 to cause at least some ofthe depicted functionality to be performed. Turning to FIG. 2A, in step1, rack device manager 100 may discover rack devices 111 for which itmay provide airflow management. For example, an administrator mayinterface with rack device manager 100 to cause rack device manager 100to use a discovery tool (e.g., Dell EMC's OpenManage Enterprise systemsmanagement console) to issue discovery requests to each rack device 111(and possibly each rack 110) in a datacenter or other location. As aresult, rack device manager 100 can receive discovery responses fromrack devices 111 containing information about each rack device (e.g., anidentifier of the rack device, an IP address, etc.).

Turning to FIG. 2B, in step 2, rack device manager 100 may use thediscovery responses (or other input containing similar information aboutrack devices 111) to create a representation of the physical location ofrack devices 111. For example, rack device manager 100 may create one ormore location data structures 201 that define a hierarchicalrepresentation of a datacenter, rooms within the datacenter, aisleswithin rooms, racks in aisles, and rack devices in racks. In someembodiments, an administrator may employ a tool such as the OpenManageEnterprise Power Manager as part of creating location data structure(s)201.

Turning to FIG. 2C, in step 3, rack device manager 100 can maintain anidentification of workloads and clusters of rack devices 111 that runthe workloads. For example, rack device manager 100 could receiveworkload and cluster information in any suitable manner, includingmanual input, and create one or more workload data structures 202 whichidentify each workload, which rack devices 111 form a cluster forhosting the workload and a priority of the workload.

At this point, rack device manager 100 will have location datastructure(s) 201 which it may use to determine where a rack device 111is physically located, including determining which rack devices 111 arelocated next to one another, and will have workload data structure(s)202 which it may use to determine which rack devices 111 form a clusterfor hosting a particular workload. Rack device manager 100 may updatelocation data structure(s) 201 and/or workload data structure(s) 202periodically or as appropriate to reflect a current location/state ofrack devices 111 and the workloads they host.

FIGS. 3A-3C provide an example of how rack device manager 100 maygenerate a rack device classifier for each rack device 111 for which itmanages airflow. Rack device manager 100 may use these rack deviceclassifiers to determine how to remediate an airflow deficiencyscenario.

Turning to FIG. 3A, in step 1, rack device manager 100 can periodicallyretrieve airflow metrics for rack devices 111. In FIG. 3A, only one rack110-1 is shown to simplify the illustration. In some embodiments, theairflow metrics can include one or more of a power consumption of therack device, an inlet temperature of the rack device, an exhausttemperature of the rack device and/or a net airflow of the rack device.Rack device manager 100 may use any suitable management interface toretrieve the airflow metrics.

Turning to FIG. 3B, in step 2, rack device manager 100 may employ anairflow estimator module 100 a to calculate an estimated airflow foreach rack device 111 based on the respective airflow metrics. In someembodiments, the estimated airflow can be calculated using the powerconsumption and the difference between the inlet and exhausttemperatures such as:

Estimated Airflow(CFM)=M*(Power Consumption)/(Exhaust Temp−Inlet Temp)

where Power Consumption is in watts and M is a multiplier having a valuethat depends on whether the temperatures are in Fahrenheit or Celsius.For example, M may be 3.2 for Fahrenheit and 1.78 for Celsius.

In cases where the airflow metrics include the power consumption but notthe inlet and exhaust temperatures of the rack device 111, airflowestimator module 100 a could calculate the estimated airflow based onthe power consumption alone such as:

Estimated Airflow(CFM)=9*(Power Consumption)/100

Accordingly, the estimated airflow for a rack device 111 is an estimateof the airflow at the rack device based on the rack device's powerconsumption and inlet and exhaust temperatures or based on the rackdevice's power consumption alone.

Turning to FIG. 3C, in step 3, rack device manager 100 may employ a rackdevice classifier module 100 b to generate a rack device classifier foreach rack device 111 based on their respective airflow metrics andestimated airflows. In some embodiments, a rack device classifier may begenerated based on two parameters, an airflow deficiency parameter (ΔAirflow) and a power headroom parameter (ΔPower) which may be calculatedas follows:

ΔAirflow=Estimated Airflow−Net Airflow

ΔPower=Maximum Power Threshold−Power Consumption

where the maximum power threshold can be a defined maximum power thatthe rack device is allowed to consume.

FIG. 4 provides an example of how rack device classifier module 100 bmay use the airflow deficiency parameter and the power headroomparameter to generate a rack device classifier. As shown, the rackdevice classifier for a rack device 111 could be set to one of fiveclassifications. The rack device classifier may fall in classification 1when the airflow deficiency parameter is between 0 and a positivethreshold and the power headroom parameter is below a threshold.Classification 1 represents optimal operation because the rack device isheavily loaded and its airflow is appropriate for the load.

The rack device classifier may fall in classification 2 when the airflowdeficiency parameter exceeds the positive threshold but the powerheadroom parameter is below the threshold. Classification 2 thereforerepresents a scenario where the rack device may be heavily loaded butits airflow is still excessive.

The rack device classifier may fall in classification 3 when the airflowdeficiency parameter is not negative and the power headroom parameter isabove the threshold. Classification 3 therefore represents a scenariowhere the rack device is underutilized and has excessive airflow.

The rack device classifier may fall in classification 4 when the airflowdeficiency parameter is negative and the power headroom parameter isabove the threshold. Classification 4 therefore represents a scenariowhere the rack device is underutilized and has insufficient airflow.

The rack device classifier may fall in classification 5 when the airflowdeficiency parameter is negative and the power headroom parameter isbelow the threshold. Classification 5 therefore represents a scenariowhere the rack device is heavily loaded and has insufficient airflow.

In the example provided in FIG. 4 , classifications 4 and 5 represent apossible airflow deficiency scenario. However, other schemes could beused for the rack device classifier. In any case, rack device manager100 can generate the rack device classifiers so that it may use them todetermine how to remediate airflow deficiency scenarios.

FIGS. 5A-5E provide an example of how rack device manager 100 mayattempt to remediate an airflow deficiency. Various actions are depictedin this example but not all actions need to be taken in any particularscenario. The example is intended to provide an overview of possibleactions that rack device manager 100 may take when addressing airflowdeficiencies that it may detect.

Turning to FIG. 5A, it is assumed that rack devices 111-1 through 111-3were assigned rack device classifiers of classification 1,classification 5 and classification 2 respectively. Based on theseassumptions, in step 1, rack device manager 100 may determine that theairflow of rack device 111-2 is deficient. In particular, rack devicemanager 100 may determine that the rack device classifier it generatedfor rack device 111-2 is indicative of an airflow deficiency.

Turning to FIG. 5B, in step 2, rack device manager 100 may check thestatus of the fan(s) on rack device 111-2 in some embodiments. Forexample, rack device manager 100 may use an access control techniquesuch as Dell's Integrated Remote Access Controller (iDRAC) to determinewhether any fan on rack device 111-2 has malfunctioned. If so, rackdevice manager 100 may conclude that the airflow deficiency has beencaused by the fan malfunction and may generate an alert in step 2 a tocomplete the process of remediating the airflow deficiency scenario.However, if the fan(s) have not malfunctioned, rack device manager 100can proceed with the process of attempting to automatically remediatethe airflow deficiency.

Turning to FIG. 3 , and assuming that the fan(s) on rack device 111-2are functioning properly, in step 3, rack device manager 100 mayidentify which rack devices 111 are neighbors to rack device 111-2. Forexample, rack device manager 100 may access location data structure(s)201 to identify which rack devices 111 are immediately adjacent rackdevice 111-2, which rack devices 111 are in the same rack as rack device111-2, etc. In this example, it is assumed that rack device manager 100determines that rack devices 111-1 and 111-3 are each immediatelyadjacent rack device 111-2 (e.g., above and below rack device 111-2).Therefore, in step 4, rack device manager 100 can retrieve the rackdevice classifier that it generated for rack devices 111-1 and 111-3 (orfor any other neighbor of rack device 111-2). In this example, rackdevice manager 100 would determine that rack device 111-3 has a rackdevice classifier of classification 3 and, because this classificationrepresents excess airflow at rack device 111-3, may determine that rackdevice 111-3 may be inducing the airflow deficiency in rack device 111-2by creating an air void.

Turning to FIG. 5D, in step 5, rack device manager 100 can obtainworkload information for rack devices 111-2 and 111-3. This steprepresents that rack device manager 100 may obtain workload informationfor a rack device 111 that is experiencing an airflow deficiency and forany neighboring rack device 111 that may be the cause of the airflowdeficiency. Notably, there need not be a neighboring rack device 111that may be causing an airflow deficiency. The rack device 111experiencing the airflow deficiency may itself be the cause of theairflow deficiency. Also, in some scenarios, more than one neighboringrack device 111 or possibly all rack devices 111 in a rack 110 could beexperiencing airflow deficiencies. Therefore, the depicted exampleshould be considered as one of possibly many different airflowdeficiency scenarios that could be addressed using the techniques of thepresent invention.

In this example, it is assumed that rack device 111-2 is hostingworkload 1 which has a high priority, while rack device 111-3 is hostingworkload 2 which has a low priority. Although not shown, as part of step5, rack device manager 100 could also identify other rack devices 111that are in the same cluster as rack device 111-2 or rack device 111-3.For example, rack device manager 100 could identify all rack devices 111that are hosting workload 1.

FIG. 5E provides various examples of actions that rack device manager100 could take to attempt to remediate the airflow deficiency scenariothat rack device 111-2 is experiencing. As one example, in step 6 a,rack device manager 100 may migrate at least some of rack device 111-2'sworkload to another rack device 111 in the cluster, which is assumed tobe rack device 111-n in this example. For example, rack device manager100 could determine, from the rack device classifier generated for rackdevice 111-n, that rack device 111-n is lightly loaded and hassufficient airflow (e.g., if its rack device classifier wereclassification 3). In such a case, rack device manager 100 could migratesome of rack device 111-2's load pertaining to workload 1 to rack device111-n to thereby cause rack device 111-2's power consumption to bereduced which may in turn cause its current airflow to be adequate.

As another example, in step 6 b, rack device manager 100 may apply apower cap to rack device 111-2. By applying a power cap to rack device111-2, rack device manager 100 could cause the current airflow to beadequate for rack device 111-2. In some embodiments, rack device manager100 may apply a power cap to a neighboring rack device 111 only when theneighboring rack device 111 is hosting a workload that does not have ahigh priority or otherwise based on the priority of the workload.

As another example, in step 6 c, rack device manager 100 may apply apower cap to rack device 111-3. By applying a power cap to rack device111-3, rack device manager 100 could cause rack device 111-3 to reduceits airflow which may in turn remediate the airflow deficiency at rackdevice 111-2 (e.g., by eliminating an air void in front of rack device111-2).

Rack device manager 100 could take any or all of the example actionsrepresented in steps 6 a-6 c to attempt to remediate the airflowdeficiency at rack device 111-2. Rack device manager 100 could performsuch actions at the same time or sequentially.

Although not depicted, in some embodiments, rack device manager 100could automatically interface with a cooling system to adjust theambient air temperature within a room such as when rack device manager100 determines that all or most rack devices 111 in the room areexperiencing airflow deficiencies and/or when the intake air temperatureis too high.

If none of these automatic actions are successful, or if rack devicemanager 100 determines that an airflow deficiency is likely a result ofa physical obstruction, rack device manager 100 may raise an alert instep 6 d to cause an administrator to investigate. In some embodiments,if the cooling system is functioning in an optimal manner and all ormany rack devices 111 are experiencing airflow deficiencies, rack devicemanager 100 may use the alert to notify an administrator that the rackdevices 111 should be reorganized to avoid excessive heating in a singlerack, aisle or room.

As can be seen, rack device manager 100 can take a number of actionsautomatically to attempt to remediate an airflow deficiency scenarioand/or may notify an administrator to provide context and guidance onhow to best remediate an airflow deficiency when automatic action may beinsufficient or ineffective. By managing airflow deficiency scenarios inthis manner, rack device manager 100 can minimize the likelihood of arack device 111 being damaged due to excessive heating and can alsoenhance the performance and efficiency of workloads.

In summary, rack device manager 100 may detect an airflow deficiencyscenario on a rack device 111 using a comparison between an estimatedairflow and net airflow of the rack device, such as by generating a rackdevice classifier. When rack device manager 100 detects an airflowdeficiency scenario, such as when net airflow is less than estimatedairflow which could be represented by a rack device classifier having aparticular value, it may consider whether neighboring rack devices maybe the cause and may take action such as by redistributing workload orapplying power caps to attempt to remediate the deficiency. When rackdevice manager 100 detects airflow deficiency scenarios at many or allof the rack devices 111 in a rack 110, it may recalibrate a coolingsystem to direct more airflow to the rack and/or may recommendreorganizing the rack devices. If automatic remediation is unsuccessfulor inappropriate, rack device manager 100 may alert an administrator toperform manual remediation such as by removing a physical obstruction.

Embodiments of the present invention may comprise or utilize specialpurpose or general-purpose computers including computer hardware, suchas, for example, one or more processors and system memory. Embodimentswithin the scope of the present invention also include physical andother computer-readable media for carrying or storingcomputer-executable instructions and/or data structures. Suchcomputer-readable media can be any available media that can be accessedby a general purpose or special purpose computer system.

Computer-readable media are categorized into two disjoint categories:computer storage media and transmission media. Computer storage media(devices) include RAM, ROM, EEPROM, CD-ROM, solid state drives (“SSDs”)(e.g., based on RAM), Flash memory, phase-change memory (“PCM”), othertypes of memory, other optical disk storage, magnetic disk storage orother magnetic storage devices, or any other similar storage mediumwhich can be used to store desired program code means in the form ofcomputer-executable instructions or data structures and which can beaccessed by a general purpose or special purpose computer. Transmissionmedia include signals and carrier waves. Because computer storage mediaand transmission media are disjoint categories, computer storage mediadoes not include signals or carrier waves.

Computer-executable instructions comprise, for example, instructions anddata which, when executed by a processor, cause a general-purposecomputer, special purpose computer, or special purpose processing deviceto perform a certain function or group of functions. The computerexecutable instructions may be, for example, binaries, intermediateformat instructions such as assembly language or P-Code, or even sourcecode.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, tablets, smart watches, pagers, routers, switches, and the like.

The invention may also be practiced in distributed system environmentswhere local and remote computer systems, which are linked (either byhardwired data links, wireless data links, or by a combination ofhardwired and wireless data links) through a network, both performtasks. In a distributed system environment, program modules may belocated in both local and remote memory storage devices. An example of adistributed system environment is a cloud of networked servers or serverresources. Accordingly, the present invention can be hosted in a cloudenvironment.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description.

What is claimed:
 1. A method for identifying and remediating an airflowdeficiency scenario on a rack device, the method comprising: detectingthat a first rack device is experiencing an airflow deficiency scenario;determining that a second rack device is a neighbor to the first rackdevice and has excess airflow; and automatically performing one or moreactions to remediate the airflow deficiency scenario.
 2. The method ofclaim 1, wherein detecting that the first rack device is experiencingthe airflow deficiency scenario comprises detecting that a net airflowof the first rack device is less than an estimated airflow for the firstrack device.
 3. The method of claim 2, wherein the estimated airflow forthe first rack device is calculated using a power consumption of thefirst rack device.
 4. The method of claim 3, wherein the estimatedairflow for the first rack device is also calculated using an inlettemperature and an exhaust temperature of the first rack device.
 5. Themethod of claim 1, wherein detecting that the first rack device isexperiencing the airflow deficiency scenario comprises generating a rackdevice classifier for the first rack device.
 6. The method of claim 5,wherein detecting that the first rack device is experiencing the airflowdeficiency scenario comprises determining that the rack deviceclassifier for the first rack device has a classification representinginsufficient airflow.
 7. The method of claim 6, wherein determining thatthe second rack device has excess airflow comprises generating a rackdevice classifier for the second rack device.
 8. The method of claim 7,wherein determining that the second rack device has excess airflowcomprises determining that the rack device classifier for the secondrack device has a classification representing excess airflow.
 9. Themethod of claim 1, wherein automatically performing one or more actionsto remediate the airflow deficiency scenario comprises redistributingworkload on the first rack device to another rack device.
 10. The methodof claim 1, wherein automatically performing one or more actions toremediate the airflow deficiency scenario comprises applying a power capto one or both of the first rack device or the second rack device. 11.The method of claim 1, wherein automatically performing one or moreactions to remediate the airflow deficiency scenario comprisesrecalibrating a cooling system.
 12. The method of claim 1, furthercomprising: generating an alert to notify an administrator of theairflow deficiency scenario.
 13. One or more computer storage mediastoring computer executable instructions which when executed implement amethod for identifying and remediating an airflow deficiency scenario ona rack device, the method comprising: obtaining airflow metrics from aplurality of rack devices; generating a rack device classifier for eachof the plurality of rack devices based on the respective airflowmetrics; identifying an airflow deficiency scenario on at least one ofthe plurality of rack devices based on the respective rack deviceclassifier; and performing one or more actions to automaticallyremediate the airflow deficiency scenario.
 14. The computer storagemedia of claim 13, wherein generating the rack device classifier foreach of the plurality of rack devices based on the respective airflowmetrics comprises calculating an estimated airflow for each of theplurality of devices.
 15. The computer storage media of claim 13,wherein performing the one or more actions to automatically remediatethe airflow deficiency scenario comprises one or more of: redistributingworkload on the at least one of the plurality of rack devices; orapplying one or more power caps to the plurality of rack devices. 16.The computer storage media of claim 15, wherein applying the one or morepower caps to the plurality of rack devices comprises applying a powercap to a neighboring rack device that has excess airflow.
 17. A systemfor identifying and remediating an airflow deficiency scenario on a rackdevice, the system comprising: one or more processors; and one or morecomputer storage media storing computer executable instructions whichwhen executed by the one or more processors implement a method foridentifying and remediating an airflow deficiency scenario on a rackdevice, the method comprising: generating a rack device classifier foreach of the plurality of rack devices in a rack; determining that therack device classifier generated for a first rack device of theplurality of rack devices is indicative of an airflow deficiencyscenario; determining that a second rack device of the plurality of rackdevices is a neighbor of the first rack device; and performing one ormore actions on the second rack device to automatically remediate theairflow deficiency scenario.
 18. The system of claim 17, wherein the oneor more actions comprise applying a power cap to the second rack device.19. The system of claim 18, wherein the power cap is applied to thesecond rack device in response to determining that the second rackdevice hosts a workload that does not have a high priority.
 20. Thesystem of claim 17, wherein the method further comprises: performing oneor more actions on the first rack device to automatically remediate theairflow deficiency scenario.